Big Data:Principles and best practices of scalable realtime data systems Paperback – 14 May 2015

Bid Data and technologies around this subject can be very hard and low-level to understand.With this book i found it clear, concise and explained in such a way that everyone with little or no background in IT can understand.A very good Big Data insight and also helpful for understanding which are the best tools to achieve good results with Hadoop and other technologies.I found it very interesting, well written and pleasant to read as well. This book helped me a lot and i'm sure it can help a lot beginners with this subject.

I really like this book, because you learn a lot since the very start of it.Not too many programming details, but that is good because it gives you an understanding of the general picture.

Good

Excellent book; it explains the Lambda Architecture in a clear, concise manner with practical tips, tricks and examples

Interesting book providing a high-level intro to BD architecture.

Help, my entire technology ecosystem has just changed under my feet in the last few years (again). I need to rapidly get upto speed on what the new tools are, how everything fits together, and how to solve common problem types. I need to know where to get started to start learning and exploring in this new technology.This book is a comprehensive overview of Lambda Architecture (Batch View, Serving Layer, Speed Layer) and the Big Data ecosystem of tools (Hadoop, MapReduce, JCasalog, Kafka, Trident, Zookeeper, Storm, Cassandra, ElephantDB, HpyerLogLog, Bloom Filters, Functional and Distributed Programming)It took a few days to read this book cover to cover. It describes an example real-time data analytics application capable of working on terabyte+ datasets, in a clustered server environments. Each chapter alternates between the high level design architecture of each piece, then a second chapter focusing on implementation details with code samples in each of the above technologies.I would recommend having an additional read of the website documentation for each tool.

All I was interested to know was how do you manage data integrity with incremental load in Lambda Architecture if you do not need a Speed layer. The answer is you do not process data incrementally, you process the entire data set which obviously isn't practical. I feel that the architecture is probably more suited to solving specific type of problems. The idea that I liked was having an Immutable Layer which you can replay and reprocess to build all the facts when things go wrong.

This is a modern, scale-out, data ingestion and processing architecture book, complete with illustrative code samples. It's beautifully written and crafted, and the narrative offers a compelling justification for the 'lambda architecture' style of implementation.I hope that over time it comes to be regarded as the "K&R" or "Gang of Four" architectural reference book for Big Data implementations. It certainly deserves to be.